A central problem in designing and implementing a data transmission system is simultaneous transmission and reception of signals from several simultaneous users such that the signals interfere with one another as little as possible. Because of this and the transmission capacity used, various transmission protocols and multiple access methods have been used, the most common especially in mobile phone traffic being FDMA and TDMA, and recently CDMA.
CDMA is a multiple access method based on a spread spectrum technique, and it has been recently put; into use in cellular radio systems in addition to previously used FDMA and TDMA. CDMA has many advantages over the prior methods, such as simplicity of frequency planning, and spectrum efficiency.
In a CDMA method, a narrow-band data signal of a user is multiplied to a relatively broadband by a spreading code having a much broader band than the data signal. Bandwidths used in known test systems include e.g. 1.25 MHz, 10 MHz and 25 MHz. The multiplication spreads the data signal over the entire band to be used. All the users transmit simultaneously on the same frequency band. On each connection between a base station and a mobile station is used a different spreading code, and the signals of the users can be distinguished from one another in the receivers on the basis of the spreading code of the user. If possible, the spreading codes are selected in such a way that they are mutually orthogonal, i.e. they do not correlate with one another.
Correlators in conventionally implemented CDMA receivers are synchronized with a desired signal, which they recognize on the basis of the spreading code. In the receiver the data signal is restored to the original band by multiplying it by the same spreading code as in the transmission step. Ideally, the signals that have been multiplied by some other spreading code do not correlate and are not restored to the narrowband. In view of the desired signal, they thus appear as noise. The object is to detect the signal of the desired user from among a number of interfering signals. In practice, the spreading codes correlate, and the signals of the other users make it more difficult to detect the desired signal by distorting the received signal. This interference caused by the users to one another is called. multiple access interference.
In a data transmission method in which a TDM multiple access method is applied several frequencies are used, each frequency being divided into time slots in which the signals of the different users are placed. Each user is thus assigned a time slot of its own. Since the frequency band reserved for the system is usually limited, the frequencies used must be repeated in the cells located at a certain distance. To achieve high frequency efficiency, the distance must be held as short as possible. It follows from this that transmissions sent at the same frequencies interfere with one another. In a certain time slot, not only the desired signal but also a noise signal is heard in the receiver, the noise signal being caused by some other connection using the same frequency.
The one-frequency detection method described above in connection with CDMA is not optimal, since the information contained in the signals of the other users is not taken into account in the detection. In addition, conventional detection cannot correct errors caused by partly non-orthogonal spreading codes and distortion of the signal over the radio path. In an optimal receiver, the information contained in the signals of all the users is taken into account, so the signals can be detected optimally using e.g. a Viterbi algorithm. The advantage of this detection method e.g. in a CDMA system is that the situation in the receiver resembles a one user CDMA system where there is no multiple access interference. For example, a near-far problem, which is typical of CDMA systems, does not arise. A near-far problem is a situation where the transmission from a transmitter close to the receiver blankets the more distant transmitters. The major drawback of the Viterbi algorithm is that the calculating efficiency that it requires increases exponentially as the number of the users rises. For example, with QPSK modulation, a ten-user system with a bit rate of 100 kbit/s would require 105 million operations per second in calculating the Viterbi algorithm. In practice, this makes it impossible to implement an optimal receiver.
It is possible to approximate, however, to an optimal receiver by different methods. Prior art teaches various methods for simultaneous multiuser detection (MUD). The best known of such methods are linear multiuser detection, a decorrelating detector and a multistage detector. These methods are described in greater detail in Varanase, Aazhang, `Multistage detection for asynchronous code division multiple access communications,` IEEE Transactions on Communications, Vol. 38, pp. 509-519, April 1990; Lupas, Verdu, `Linear multiuser detectors for synchronous code-division multiple access channels,` IEEE Transactions on Information Theory, Vol. 35, No. 1, pp. 123-136, January 1989; and Lupas, Verdu, `Near-far resistance of multiuser detectors in asynchronous channels,` IEEE Transactions on Communications, Vol. 38, April 1990. These methods, however, also involve many operations, such as matrix inversion operations, that require a high calculating capacity.
Another way of solving the problems caused by multiple access interference is to use interference cancellation (IC) methods. In IC-type solutions, the users are detected individually, if possible, and often in the order of magnitude, in such a way that the effect of the signals of the already detected users is canceled from the received transmission before the next user is detected. An example for a solution of this kind is described in EP 491,668, where a procedure of the type described above is applied in a CDMA cellular radio system. Noise cancellation methods are more effective than MUD-type algorithms with respect to calculation, but their performance is lower especially in difficult reception conditions, such as in a fading multipath channel, where signals are often weak.